Stochastic programming : modeling decision problems under uncertainty / Willem K. Klein Haneveld, Maarten H. van der Vlerk, Ward Romeijnders.

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Stochastic programming : modeling decision problems under uncertainty / Willem K. Klein Haneveld, Maarten H. van der Vlerk, Ward Romeijnders.

9783030292195 (electronic book)
3030292193 (electronic book)
9783030292188

https://doi.org/10.1007/978-3-030-29219-5
https://doi.org/10.1007/978-3-030-29

Cham, Switzerland : Springer, [2020]

English

1 online resource (xii, 249 pages) : illustrations.

10.1007/978-3-030-29219-5 doi
10.1007/978-3-030-29

T57.79

519.7

This book provides an essential introduction to Stochastic Programming, especially intended for graduate students. The book begins by exploring a linear programming problem with random parameters, representing a decision problem under uncertainty. Several models for this problem are presented, including the main ones used in Stochastic Programming: recourse models and chance constraint models. The book not only discusses the theoretical properties of these models and algorithms for solving them, but also explains the intrinsic differences between the models. In the book's closing section, several case studies are presented, helping students apply the theory covered to practical problems. The book is based on lecture notes developed for an Econometrics and Operations Research course for master students at the University of Groningen, the Netherlands - the longest-standing Stochastic Programming course worldwide.

Includes bibliographical references and index.

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Online resource; title from PDF title page (SpringerLink, viewed October 30, 2019).

Graduate texts in operations research.

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